Open AccessA method of generative model design based on irregular data in application to heat transfer problems
Author(s) -
Nikolay Bykov,
Alexander Hvatov,
Anna V. Kalyuzhnaya,
Alexander V. Boukhanovsky
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1959/1/012012
Subject(s) - partial differential equation , polygon mesh , process (computing) , computer science , construct (python library) , finite element method , differential (mechanical device) , heat transfer , thermal conduction , data model (gis) , algorithm , mathematical optimization , mathematics , artificial intelligence , engineering , mathematical analysis , physics , computer graphics (images) , materials science , structural engineering , composite material , thermodynamics , programming language , aerospace engineering , operating system
The paper presents the results of applying the generative design method to reconstruct a model driven by irregular data in the form of a partial differential equation. The problem of non-stationary heating of a metal rod is considered as an example. The finite element method is used to construct templates of possible elements of the derived differential equation. The optimization algorithm for determining a model design is based on the procedure of best subset selection. The efficiency of the method for derivating a model of the thermal conduction process based on irregular data is shown. As irregular data, data obtained on spatial meshes with alternating steps of different size, or a step changing in arithmetic progression, are considered.